Circulating T cells: a promising biomarker of anti-PD-(L)1 therapy.

Anti-PD-(L)1 therapy has shown great efficacy in some patients with cancer. However, a significant proportion of patients with cancer do not respond to it. Another unmet clinical need for anti-PD-(L)1 therapy is the dynamic monitoring of treatment effects. Therefore, identifying biomarkers that can stratify potential responders before PD-(L)1 treatment and timely monitoring of the efficacy of PD-(L)1 treatment are crucial in the clinical setting. The identification of biomarkers by liquid biopsy has attracted considerable attention. Among the identified biomarkers, circulating T cells are one of the most promising because of their indispensable contribution to anti-PD-(L)1 therapy. The present review aimed to thoroughly explore the potential of circulating T cells as biomarkers of anti-PD-(L)1 therapy and its advantages and limitations.

Preserving shape details of pulse signals for video-based blood pressure estimation.

In recent years, imaging photoplethysmograph (iPPG) pulse signals have been widely used in the research of non-contact blood pressure (BP) estimation, in which BP estimation based on pulse features is the main research direction. Pulse features are directly related to the shape of pulse signals while iPPG pulse signals are easily disturbed during the extraction process. To mitigate the impact of pulse feature distortion on BP estimation, it is necessary to eliminate interference while retaining valuable shape details in the iPPG pulse signal. Contact photoplethysmograph (cPPG) pulse signals measured at rest can be considered as the undisturbed reference signal. Transforming the iPPG pulse signal to the corresponding cPPG pulse signal is a method to ensure the effectiveness of shape details. However, achieving the required shape accuracy through direct transformation from iPPG to the corresponding cPPG pulse signals is challenging. We propose a method to mitigate this challenge by replacing the reference signal with an average cardiac cycle (ACC) signal, which can approximately represent the shape information of all cardiac cycles in a short time. A neural network using multi-scale convolution and self-attention mechanisms is developed for this transformation. Our method demonstrates a significant improvement in the maximal information coefficient (MIC) between pulse features and BP values, indicating a stronger correlation. Moreover, pulse signals transformed by our method exhibit enhanced performance in BP estimation using different model types. Experiments are conducted on a real-world database with 491 subjects in the hospital, averaging 60 years of age.

Predicting Arterial Stiffness from Single-Channel Photoplethysmography Signal: A Feature Interaction-Based Approach.

Arterial stiffness (AS) serves as a crucial indicator of arterial elasticity and function, typically requiring expensive equipment for detection. Given the strong correlation between AS and various photoplethysmography (PPG) features, PPG emerges as a convenient method for assessing AS. However, the limitations of independent PPG features hinder detection accuracy. This study introduces a feature selection method leveraging the interactive relationships between features to enhance the accuracy of predicting AS from a single-channel PPG signal. Initially, an adaptive signal interception method was employed to capture high-quality signal fragments from PPG sequences. 58 PPG features, deemed to have potential contributions to AS estimation, were extracted and analyzed. Subsequently, the interaction factor (IF) was introduced to redefine the interaction and redundancy between features. A feature selection algorithm (IFFS) based on the IF was then proposed, resulting in a combination of interactive features. Finally, the Xgboost model is utilized to estimate AS from the selected features set. The proposed approach is evaluated on datasets of 268 male and 124 female subjects, respectively. The results of AS estimation indicate that IFFS yields interacting features from numerous sources, rejects redundant ones, and enhances the association. The interaction features combined with the Xgboost model resulted in an MAE of 122.42 and 142.12 cm/sec, an SDE of 88.16 and 102.56 cm/sec, and a PCC of 0.88 and 0.85 for the male and female groups, respectively. The findings of this study suggest that the stated method improves the accuracy of predicting AS from single-channel PPG, which can be used as a non-invasive and cost-effective screening tool for atherosclerosis.

Probing the stability of metal-organic frameworks by structure-responsive mass spectrometry imaging.

The widespread application of metal-organic frameworks (MOFs) is seriously hindered by their structural instability and it is still very challenging to probe the stability of MOFs during application by current techniques. Here, we report a novel structure-responsive mass spectrometry (SRMS) imaging technique to probe the stability of MOFs. We discovered that intact CuBTC (as a model of MOFs) could generate the characteristic peaks of organic ligands and carbon cluster anions in laser desorption/ionization mass spectrometry, but these peaks were significantly changed when the structure of CuBTC was dissociated, thus enabling a label-free probing of the stability. Furthermore, SRMS can be performed in imaging mode to visualize the degradation kinetics and reveal the spatial heterogeneity of the stability of CuBTC. This technique was successfully applied in different application scenarios (in water, moist air, and CO2) and also validated with different MOFs. It thus provides a versatile new tool for better design and application of environment-sensitive materials.

HRUNet: Assessing Uncertainty in Heart Rates Measured from Facial Videos.

Video-based Photoplethysmography (VPPG) offers the capability to measure heart rate (HR) from facial videos. However, the reliability of the HR values extracted through this method remains uncertain, especially when videos are affected by various disturbances. Confronted by this challenge, we introduce an innovative framework for VPPG-based HR measurements, with a focus on capturing diverse sources of uncertainty in the predicted HR values. In this context, a neural network named HRUNet is structured for HR extraction from input facial videos. Departing from the conventional training approach of learning specific weight (and bias) values, we leverage the Bayesian posterior estimation to derive weight distributions within HRUNet. These distributions allow for sampling to encode uncertainty stemming from HRUNet's limited performance. On this basis, we redefine HRUNet's output as a distribution of potential HR values, as opposed to the traditional emphasis on the single most probable HR value. The underlying goal is to discover the uncertainty arising from inherent noise in the input video. HRUNet is evaluated across 1,098 videos from seven datasets, spanning three scenarios: undisturbed, motion-disturbed, and light-disturbed. The ensuing test outcomes demonstrate that uncertainty in the HR measurements increases significantly in the scenarios marked by disturbances, compared to that in the undisturbed scenario. Moreover, HRUNet outperforms state-of-the-art methods in HR accuracy when excluding HR values with 0.4 uncertainty. This underscores that uncertainty emerges as an informative indicator of potentially erroneous HR measurements. With enhanced reliability affirmed, the VPPG technique holds the promise for applications in safety-critical domains.

Metabolite-sensing GPCRs in rheumatoid arthritis.

Persistent inflammation in damaged joints results in metabolic dysregulation of the synovial microenvironment, causing pathogenic alteration of cell activity in rheumatoid arthritis (RA). Recently, the role of metabolite and metabolite-sensing G protein-coupled receptors (GPCRs) in the RA-related inflammatory immune response (IIR) has become a focus of research attention. These GPCRs participate in the progression of RA by modulating immune cell activation, migration, and inflammatory responses. Here, we discuss recent evidence implicating metabolic dysregulation in RA pathogenesis, focusing on the connection between RA-related IIR and GPCR signals originating from the synovial joint and gut. Furthermore, we discuss future directions for targeting metabolite-sensing GPCRs for therapeutic benefit, emphasizing the importance of identifying endogenous ligands and investigating the various transduction mechanisms involved.

Mechanisms of rainfall-induced landslides and interception dynamic response: a case study of the Ni changgou landslide in Shimian, China.

Geological hazards, especially landslides and mudslides, are frequent in Caoke County, Sichuan Province, China. In September 2022, the mechanical parameters of the soil were obtained through a basic investigation of the landslide characteristics of Ni changgou. Upon that, the finite element-discrete element method was used to reconstruct the three-dimensional numerical model of the landslide on the right bank of Ni changgou, and the initiation mechanism of rainfall on landslide and the formation of debris flow impact dam process were simulated. Furthermore, the pore pressure, stability coefficient as well as displacement of the landslide body were analyzed. It turned out that with the increase of rainfall intensity, the pore water pressure value also increases, where pore water pressure rises rapidly. the slope is close to the unstable edge, Eventually, it tends to one under rainfall conditions, and due to gravity, the slide of the landslide is induced. The duration of landslide movement is about 200 s, the maximum average velocity of the landslide reaches 4.85 m/s, and the average movement distance is close to 500 m. In addition, this method is applied to the Chutougou debris flow, and the corresponding hazard analysis is added which could better show the treatment and application of debris flow in actual engineering.

GRK2 inhibits Flt-1+ macrophage infiltration and its proangiogenic properties in rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease with a complex etiology. Monocyte-derived macrophages (MDMs) infiltration are associated with RA severity. We have reported the deletion of G-protein-coupled receptor kinase 2 (GRK2) reprograms macrophages toward an anti-inflammatory phenotype by recovering G-protein-coupled receptor signaling. However, as more GRK2-interacting proteins were discovered, the GRK2 interactome mechanisms in RA have been understudied. Thus, in the collagen-induced arthritis mouse model, we performed genetic GRK2 deletion using GRK2f/fLyz2-Cre+/- mice. Synovial inflammation and M1 polarization were improved in GRK2f/fLyz2-Cre+/- mice. Supporting experiments with RNA-seq and dual-luciferase reporter assays identified peroxisome proliferator-activated receptor γ (PPARγ) as a new GRK2-interacting protein. We further confirmed that fms-related tyrosine kinase 1 (Flt-1), which promoted macrophage migration to induce angiogenesis, was inhibited by GRK2-PPARγ signaling. Mechanistically, excess GRK2 membrane recruitment in CIA MDMs reduced the activation of PPARγ ligand-binding domain and enhanced Flt-1 transcription. Furthermore, the treatment of mice with GRK2 activity inhibitor resulted in significantly diminished CIA pathology, Flt-1+ macrophages induced-synovial inflammation, and angiogenesis. Altogether, we anticipate to facilitate the elucidation of previously unappreciated details of GRK2-specific intracellular signaling. Targeting GRK2 activity is a viable strategy to inhibit MDMs infiltration, affording a distinct way to control joint inflammation and angiogenesis of RA.

Involvement of Embryo-Derived and Monocyte-Derived Intestinal Macrophages in the Pathogenesis of Inflammatory Bowel Disease and Their Prospects as Therapeutic Targets.

Inflammatory bowel disease (IBD) is a group of intestinal inflammatory diseases characterized by chronic, recurrent, remitting, or progressive inflammation, which causes the disturbance of the homeostasis between immune cells, such as macrophages, epithelial cells, and microorganisms. Intestinal macrophages (IMs) are the largest population of macrophages in the body, and the abnormal function of IMs is an important cause of IBD. Most IMs come from the replenishment of blood monocytes, while a small part come from embryos and can self-renew. Stimulated by the intestinal inflammatory microenvironment, monocyte-derived IMs can interact with intestinal epithelial cells, intestinal fibroblasts, and intestinal flora, resulting in the increased differentiation of proinflammatory phenotypes and the decreased differentiation of anti-inflammatory phenotypes, releasing a large number of proinflammatory factors and aggravating intestinal inflammation. Based on this mechanism, inhibiting the secretion of IMs' proinflammatory factors and enhancing the differentiation of anti-inflammatory phenotypes can help alleviate intestinal inflammation and promote tissue repair. At present, the clinical medication of IBD mainly includes 5-aminosalicylic acids (5-ASAs), glucocorticoid, immunosuppressants, and TNF-α inhibitors. The general principle of treatment is to control acute attacks, alleviate the condition, reduce recurrence, and prevent complications. Most classical IBD therapies affecting IMs function in a variety of ways, such as inhibiting the inflammatory signaling pathways and inducing IM2-type macrophage differentiation. This review explores the current understanding of the involvement of IMs in the pathogenesis of IBD and their prospects as therapeutic targets.

VidBP: Detecting Blood Pressure from Facial Videos with Personalized Calibration.

Recent studies have found that blood volume pulse (BVP) in facial videos contains features highly correlated to blood pressure (BP). However, the mapping from BVP features to BP varies from person to person. To address this issue, VidBP has been proposed as a BP detector that can be calibrated based on an individual's data. VidBP is pre-trained on a large dataset to extract BP-related features from BVP. Then, BVP samples and BP labels of an individual are fed into the pre-trained VidBP to create a personal dictionary of BP-related features. When estimating the individual's BP, the current BP-related feature is compared to the features saved in the dictionary, and the BP labels of the similar features are considered as the BP estimate. The performance of VidBP was evaluated on 640 samples of 16 subjects, and it demonstrated significantly lower errors in BP estimation compared to state-of-the-art methods. The personalized calibration of VidBP is a significant advantage, enabling it to better capture the unique mapping from BVP features to BP for each individual.Clinical relevance This study reports a feasible method to estimate BP from facial videos, providing a convenient and cost-effective way for home BP monitoring.

Perspectives and new aspects of histone deacetylase inhibitors in the therapy of CNS diseases.

Many populations worldwide are suffering from central nervous system (CNS) diseases such as brain tumors, neurodegenerative diseases (Alzheimer's disease, Parkinson's disease and Huntington's disease) and stroke. There is a shortage of effective drugs for most CNS diseases. As one of the regulatory mechanisms of epigenetics, the particular role and therapeutic benefits of histone deacetylases (HDACs) in the CNS have been extensively studied. In recent years, HDACs have attracted increasing attention as potential drug targets for CNS diseases. In this review, we summarize the recent applications of representative histone deacetylases inhibitors (HDACis) in CNS diseases and discuss the challenges in developing HDACis with different structures and better blood-brain barrier (BBB) permeability, hoping to promote the development of more effective bioactive HDACis for the treatment of CNS diseases.

Extracellular matrix in synovium development, homeostasis and arthritis disease.

Extracellular matrix (ECM) is a three-dimensional network entity composed of extracellular macromolecules. ECM in synovium not only supports the structural integrity of synovium, but also plays a crucial role in regulating homeostasis and damage repair response in synovium. Obvious disorders in the composition, behavior and function of synovial ECM will lead to the occurrence and development of arthritis diseases such as rheumatoid arthritis (RA), osteoarthritis (OA) and psoriatic arthritis (PsA). Based on the importance of synovial ECM, targeted regulation of the composition and structure of ECM is considered to be an effective measure for the treatment of arthritis disease. This paper reviews the current research status of synovial ECM biology, discusses the role and mechanism of synovial ECM in physiological status and arthritis disease, and summarizes the current strategies for targeting synovial ECM to provide information for the pathogenesis, diagnosis and treatment of arthritis disease.

PFDNet: A Pulse Feature Disentanglement Network for Atrial Fibrillation Screening From Facial Videos.

Video-based Photoplethysmography (VPPG) can identify arrhythmic pulses during atrial fibrillation (AF) from facial videos, providing a convenient and cost-effective way to screen for occult AF. However, facial motions in videos always distort VPPG pulse signals and thus lead to the false detection of AF. Photoplethysmography (PPG) pulse signals offer a possible solution to this problem due to the high quality and resemblance to VPPG pulse signals. Given this, a pulse feature disentanglement network (PFDNet) is proposed to discover the common features of VPPG and PPG pulse signals for AF detection. Taking a VPPG pulse signal and a synchronous PPG pulse signal as inputs, PFDNet is pre-trained to extract the motion-robust features that the two signals share. The pre-trained feature extractor of the VPPG pulse signal is then connected to an AF classifier, forming a VPPG-driven AF detector after joint fine-tuning. PFDNet has been tested on 1440 facial videos of 240 subjects (50% AF absence and 50% AF presence). It achieves a Cohen's Kappa value of 0.875 (95% confidence interval: 0.840-0.910, P<0.001) on the video samples with typical facial motions, which is 6.8% higher than that of the state-of-the-art method. PFDNet shows significant robustness to motion interference in the video-based AF detection task, promoting the development of opportunistic screening for AF in the community.

Activation of the kynurenine-aryl hydrocarbon receptor axis impairs the chondrogenic and chondroprotective effects of human umbilical cord-derived mesenchymal stromal cells in osteoarthritis rats.

It has been proven that intra-articular injection of mesenchymal stromal cells (MSCs) can alleviate cartilage damage in osteoarthritis (OA) by differentiating into chondrocytes and protecting inherent cartilage. However, the mechanism by which the OA articular microenvironment affects MSCs' therapeutic efficiency is yet to be fully elucidated. The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor involved in various cellular processes, such as osteogenesis and immune regulation. Tryptophan (Trp) metabolites, most of which are endogenous ligand for AHR, are abnormally increased in synovial fluid (SF) of OA and rheumatoid arthritis (RA) patients. In this study, the effects of kynurenine (KYN), one of the most important metabolites of Trp, were evaluated on the chondrogenic and chondroprotective effects of human umbilical cord-derived mesenchymal stromal cells (hUC-MSCs). hUC-MSCs were cultured in conditioned medium containing different proportions of OA/RA SF, or stimulated with KYN directly, and then, AHR activation, proliferation, and chondrogenesis of hUC-MSCs were measured. Moreover, the chondroprotective efficiency of short hairpin-AHR-UC-MSC (shAHR-UC-MSC) was determined in a rat surgical OA model (right hind joint). OA SF could activate AHR signaling in hUC-MSCs in a concentration-dependent manner and inhibit the chondrogenic differentiation and proliferation ability of hUC-MSCs. Similar results were observed in hUC-MSCs stimulated with KYN in vitro. Notably, shAHR-UC-MSC exhibited superior therapeutic efficiency in OA rat upon intra-articular injection. Taken together, this study indicates that OA articular microenvironment is not conducive to the therapeutic effect of hUC-MSCs, which is related to the activation of the AHR pathway by tryptophan metabolites, and thus impairs the chondrogenic and chondroprotective effects of hUC-MSCs. AHR might be a promising modification target for further improving the therapeutic efficacy of hUC-MSCs on treatment of cartilage-related diseases such as OA.

Embryonic diapause due to high glucose is related to changes in glycolysis and oxidative phosphorylation, as well as abnormalities in the TCA cycle and amino acid metabolism.

Introduction: The adverse effects of high glucose on embryos can be traced to the preimplantation stage. This study aimed to observe the effect of high glucose on early-stage embryos. Methods and results: Seven-week-old ICR female mice were superovulated and mated, and the zygotes were collected. The zygotes were randomly cultured in 5 different glucose concentrations (control, 20mM, 40mM, 60mM and 80mM glucose). The cleavage rate, blastocyst rate and total cell number of blastocyst were used to assess the embryo quality. 40 mM glucose was selected to model high glucose levels in this study. 40mM glucose arrested early embryonic development, and the blastocyst rate and total cell number of the blastocyst decreased significantly as glucose concentration was increased. The reduction in the total cell number of blastocysts in the high glucose group was attributed to decreased proliferation and increased cell apoptosis, which is associated with the diminished expression of GLUTs (GLUT1, GLUT2, GLUT3). Furthermore, the metabolic characterization of blastocyst culture was observed in the high-glucose environment. Discussion: The balance of glycolysis and oxidative phosphorylation at the blastocyst stage was disrupted. And embryo development arrest due to high glucose is associated with changes in glycolysis and oxidative phosphorylation, as well as abnormalities in the TCA cycle and amino acid metabolism.

Non-invasive blood pressure estimation combining deep neural networks with pre-training and partial fine-tuning.

Objective. Daily blood pressure (BP) monitoring is essential since BP levels can reflect the functions of heart pumping and vasoconstriction. Although various neural network-based BP estimate approaches have been proposed, they have certain practical shortcomings, such as low estimation accuracy and poor model generalization. Based on the strategy of pre-training and partial fine-tuning, this work proposes a non-invasive method for BP estimation using the photoplethysmography (PPG) signal.Approach. To learn the PPG-BP relationship, the deep convolutional bidirectional recurrent neural network (DC-Bi-RNN) was pre-trained with data from the public medical information mark for intensive care (MIMIC III) database. A tiny quantity of data from the target subject was used to fine-tune the specific layers of the pre-trained model to learn more individual-specific information to achieve highly accurate BP estimation.Main results.The mean absolute error and the Pearson correlation coefficient (r) of the proposed algorithm are 3.21 mmHg and 0.919 for systolic BP, and 1.80 mmHg and 0.898 for diastolic BP (DBP). The experimental results show that our method outperforms other methods and meets the requirements of the Association for the Advancement of Medical Instrumentation standard, and received an A grade according to the British Hypertension Society standard.Significance.The proposed method applies the strategy of pre-training and partial fine-tuning to BP estimation and verifies its effectiveness in improving the accuracy of non-invasive BP estimation.

Mass Spectrometry Imaging Strategy for In Situ Quantification of Soot in Size-Segregated Air Samples.

Soot, mainly derived from incomplete combustion of fossil fuel and biomass, exists ubiquitously in different environmental matrixes. To study the detrimental effects of soot on climate, air quality, and human health, accurate quantification of soot is an important prerequisite. However, until now, quantification of soot in environmental media, especially in carbonaceous media, is still very challenging. Here, we report a matrix-free laser desorption/ionization mass spectrometry (LDI-MS) method for in situ imaging of soot particles in size-segregated aerosol samples collected on filter membranes. A series of round-shaped sample spots in filter membranes were selected and subjected to MS imaging analysis, enabling direct in situ quantification of soot without solvent extraction or separation. Especially, the MS imaging with serial sample spots can overcome the problems of sweet-spot in LDI-MS and inhomogeneous distribution of soot in the filter membrane, thus greatly improving the precision of quantification. The limit of detection of soot was 4 ng/m2 and the recovery was 84.4-126%. By using this method, we found that a higher soot content was present in larger-sized particulate matter than smaller-sized particles, suggesting that aerosol soot was mainly derived from primary emission sources. Furthermore, this method also shows the potential to analyze nitrate and sulfate species in PM2.5. To the best of our knowledge, it is the first method capable of simultaneous analysis of inorganic salts and soot in air samples. It represents a novel strategy for in situ quantification of aerosol soot with the advantages of high specificity, high sensitivity, separation-, solvent- and matrix-free.

Corynoxine suppresses pancreatic cancer growth primarily via ROS-p38 mediated cytostatic effects.

BACKGROUND: Pancreatic cancer is among the most common malignant tumours, and effective therapeutic strategies are still lacking. While Corynoxine (Cory) can induce autophagy in neuronal cells, it remains unclear whether Cory has anti-tumour activities against pancreatic cancer. METHODS: Two pancreatic cancer cell lines, Patu-8988 and Panc-1, were used. Effects of Cory were evaluated by cell viability analysis, EdU staining, TUNEL assay, colony formation assay, and flow cytometry. Quantitative PCR and Western blot were performed to analyse mRNA and protein levels, respectively. In vivo anti-tumour efficacy of Cory was determined by a xenograft model. RESULTS: Cory treatment inhibited cell proliferation, induced endoplasmic reticulum (ER) stress, and triggered apoptosis in the pancreatic cancer cell lines. CHOP knockdown-mediated inhibition of ER stress alleviated the Cory-induced apoptosis but showed a limited effect on cell viability. Cory induced cell death partially via promoting reactive oxygen species (ROS) production and activating p38 signalling. Pretreatment with ROS scavenger N-acetylcysteine and p38 inhibitor SB203580 relieved the Cory-induced inhibition on cell growth. Cory remarkably blocked pancreatic tumour growth in vivo. CONCLUSIONS: Cory exerts an anti-tumour effect on pancreatic cancer primarily via ROS-p38-mediated cytostatic effects. Cory may serve as a promising therapeutic agent for pancreatic cancer.

Heart rate estimation from facial videos with motion interference using T-SNE-based signal separation.

Remote photoplethysmography (RPPG) can detect heart rate from facial videos in a non-contact way. However, head movement often affects its performance in the real world. In this paper, a novel anti-motion interference method named T-SNE-based signal separation (TSS) is proposed to solve this problem. TSS first decomposes the observed color traces into pulse-related vectors and noise vectors using the T-SNE algorithm. Then, it selects the vector with the most significant spectral peak as the pulse signal for heart rate measurement. The proposed method is tested on a self-collected dataset (17 males and 8 females) and two public datasets (UBFC-RPPG and VIPL-HR). Experimental results show that the proposed method outperforms state-of-the-art methods, especially on the videos containing head movements, improving the Pearson correlation coefficient by 5% compared with the best contrasting method. To summarize, this work significantly strengthens the motion robustness of RPPG, which makes a substantial contribution to the development of video-based heart rate detection.